Predictive algorithm to stratify newborns at-risk for child undernutrition in India: Secondary analysis of the National Family Health Survey-4.

ABSTRACT:

Background

India is at the epicentre of global child undernutrition. Strategies to identify at-risk populations are needed in the context of limited resources.

Methods

Data from children under the age of five surveyed in the 2015-2016 National Family Health Survey were used. Child undernutrition was assessed using anthropometric measurements. Predictor variables were identified from the extant literature and included if they could be measured at the time of delivery. Survey-weighted logistic regression was applied to model the outcome. Internal validation of the model was performed using 200 bootstrapped samples representing half of the total data sets.

Results

In 2016, 54.4% (95% CI = 54.0%-54.8%) of Indian children were undernourished, according to a composite index

SUBMITTER: Soni A 

PROVIDER: S-EPMC9107290 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature